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Convolutional neural networks (CNNs) show superb general performance on the head pose estimation challenge below controllable situations, but their generalization ability inside the wild must be improved. To deal with this situation, we propose an technique involving the introduction of facial landmark facts in to the task simplifier and landmark h

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Second, this illustration is explicitly disentangled from other face variants for instance pose, in the pose code furnished into the decoder and pose estimation from the discriminator. Third, DR-GAN can take 1 or various illustrations or photos as being the input, and deliver 1 unified identification representation along with an arbitrary range of

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